These tracks were created using Stableaudio AI (Stableaudio). I took inspiration from genre tags on RateYourMusic and carefully crafted prompts using detailed descriptors to shape the sound. After generating the tracks, I simply downloaded the MP3 files.
Track 1: Meditative Ambient Soundscape
Style: Ambient, Post-Rock, Cinematic
Length: 2 minutes
Goal: A calm, meditative atmosphere with minimal
instrumentation.
Tags Used:
Ambient, Post-Rock, Cinematic, Ethereal, Soothing, Meditative,
Minimalist, Warm Subtle Bass, Deep Drones, Airy Pads, Textures, Analog
Synths, Field Recordings, Wind Sounds, Reverb, 60
BPM
Track 2: Energetic Breakbeat Rave
Style: Breakbeat, Acid Breaks, 90s Rave
Length: 2 minutes
Goal: A high-energy, raw breakbeat track with a chaotic
yet funky groove.
Tags Used:
Breakbeat, Acid Breaks, 90s Rave, Energetic, Raw, Funky, Chaotic,
Breakbeats, Deep Bass, Distorted 808, Acid Bass, Filtered Chords,
Reversed Pads, Vocal Chops, 135 BPM
Here’s a scatterplot of the Danceability compared to the Tempo of the tracks. My track 1 (ambient) is marked red, track 2 (breakbeat) is blue.
Findings and Final Thoughts
There appears to be no set correlation between the danceability and tempo of the tracks. However, an interesting pattern emerges: there are two clusters—one with low danceability, and another with high danceability, while the tempo does not differ much
Regarding my own tracks:
The calm ambient track has an average tempo and low danceability.
The breakbeat song has an average tempo but high danceability.
One particularly surprising observation is how the AI interpreted the second song’s tempo. While I set it to 135 BPM, it was classified as 93 BPM. This suggests that the AI might have emphasized a different rhythmic structure or half-time feel in its classification.